MacBook Pro (14-inch, 2023)
Geekbench AI Score
3277
Single Precision Score
21986
Half Precision Score
24203
Quantized Score
Geekbench AI 1.1.0 for macOS AArch64
Result Information
| User | ricnecro |
| Upload Date | October 06 2024 05:43 PM |
| Views | 13 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M2 Pro |
| System Information | |
|---|---|
| Operating System | macOS 15.0.1 (Build 24A348) |
| Model | MacBook Pro (14-inch, 2023) |
| Model ID | Mac14,9 |
| Motherboard | Mac14,9 |
| CPU Information | |
|---|---|
| Name | Apple M2 Pro |
| Topology | 1 Processor, 10 Cores |
| Identifier | Apple M2 Pro |
| Base Frequency | 2.38 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1038
193.0 IPS |
|
|
Image Classification (HP)
|
100% |
13966
2.60 KIPS |
|
|
Image Classification (Q)
|
96% |
16309
3.05 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1351
21.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
10052
162.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
11241
182.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
9862
11.5 IPS |
|
|
Pose Estimation (HP)
|
100% |
106172
123.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
103750
121.6 IPS |
|
|
Object Detection (SP)
|
100% |
1328
105.3 IPS |
|
|
Object Detection (HP)
|
99% |
14816
1.18 KIPS |
|
|
Object Detection (Q)
|
91% |
16408
1.31 KIPS |
|
|
Face Detection (SP)
|
100% |
2779
33.0 IPS |
|
|
Face Detection (HP)
|
100% |
30839
366.4 IPS |
|
|
Face Detection (Q)
|
100% |
40349
479.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
4964
38.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
85817
661.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
108865
850.7 IPS |
|
|
Style Transfer (SP)
|
100% |
19688
25.3 IPS |
|
|
Style Transfer (HP)
|
100% |
203587
261.7 IPS |
|
|
Style Transfer (Q)
|
96% |
192865
248.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4141
152.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
41395
1.53 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
49439
1.83 KIPS |
|
|
Text Classification (SP)
|
100% |
1860
2.48 KIPS |
|
|
Text Classification (HP)
|
100% |
2956
3.95 KIPS |
|
|
Text Classification (Q)
|
93% |
2937
3.94 KIPS |
|
|
Machine Translation (SP)
|
100% |
3723
64.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1813
31.2 IPS |
|
|
Machine Translation (Q)
|
98% |
1797
31.1 IPS |
